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feat(doc): recent articles first

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@ -927,8 +927,29 @@ ISBN: 978-0-470-27858-1</blockquote>
<ul class="publications">
</ul>
<h3>Accelerator Physics</h3>
<ul>
<li>E. Valetov, G. Dal Maso, P-R. Kettle, A. Knecht, A. Papa, on behalf of the HIMB Project. <a href="https://doi.org/10.3390/particles7030039">Beamline Optimisation for High-Intensity Muon Beams at PSI Using the Heterogeneous Island Model</a>. <i>Particles</i> (2024), <i>7</i>, 683-691.</li>
</ul>
<h3>Bioinformatics</h3>
<ul>
<li> Emile Zakiev, Johann Dreo, Mara Santarelli, Benno Schwikowski, <a href="https://hal.science/hal-04110700">Statistical Discovery of Transcriptomic Cancer Signatures using Multimodal Local Search</a>, <i>PGMO Days</i> (2022).</li>
</ul>
<h3>Metaheuristics Design</h3>
<ul>
<li>Johann Dreo, Carola Doerr, Amine Aziz-Alaoui, Alix Zheng, <a href="https://hal.science/hal-04110704/document">Using irace, paradiseo and iohprofiler for large-scale algorithm configuration</a>, <i>8th COnfiguration and SElection of ALgorithms (COSEAL) workshop</i> (2021).</li>
<li>Amine Aziz-Alaoui, Carola Doerr, Johann Dreo, <a href="https://arxiv.org/abs/2102.06435">Towards large scale automated algorithm design by integrating modular benchmarking frameworks</a>, <i>Proceedings of the Genetic and Evolutionary Computation Conference Companion</i> (2021).</li>
<li>Johann Dréo, Carola Doerr, Yann Semet, <a href="https://hal.sorbonne-universite.fr/hal-02179604/document">Coupling the design of benchmark with algorithm in landscape-aware solver design</a>, <i>Proceedings of the Genetic and Evolutionary Computation Conference Companion</i> (2019).</li>
<li>Johann Dreo, <a href="https://dl.acm.org/doi/10.1145/1570256.1570301">Using Performance Fronts for Parameter Setting of Stochastic Metaheuristics</a>, <i>Genetic and Evolutionary Computation Conference</i>, (2009).</li>
</ul>
<h3>Automated Planning</h3>
<ul>
<li>Mostepha Redouane Khouadjia, Marc Schoenauer, Vincent Vidal, Johann Dreo, Pierre Savéant, <a href="https://arxiv.org/abs/1305.2265v1">Quality measures of parameter tuning for aggregated multi-objective temporal planning</a>, <i>7th International Conference on Learning and Intelligent Optimization (LION 7)</i> (2013).</li>
<li>Mostepha Redouane Khouadjia, Marc Schoenauer, Vincent Vidal, Johann Dreo, Pierre Savéant, <a href="https://arxiv.org/abs/1305.1169v1">Multi-Objective AI Planning: Comparing Aggregation and Pareto Approaches</a>, <i>Conference on Evolutionary Computation in Combinatorial Optimization (EvoCOP)</i> (2013).</li>
<li>Mostepha Redouane Khouadjia, Marc Schoenauer, Vincent Vidal, Johann Dreo, Pierre Savéant, <a href="https://arxiv.org/abs/1212.5276">Multi-Objective AI Planning: Evaluating DAE-YAHSP on a Tunable Benchmark</a>, <i>7th International Conference on Evolutionary Multi-Criterion Optimization</i> (2013).</li>
<li>Jacques Bibaï, Pierre Savéant, Marc Schoenauer, Vincent Vidal, <a href="http://www.aaai.org/ocs/index.php/ICAPS/ICAPS10/paper/view/1414">An Evolutionary Metaheuristic Based on State Decomposition for Domain-Independent Satisficing Planning</a>, <i>Twentieth International Conference on Automated Planning and Scheduling </i> (2010). <strong>Winner of the International Planning Competition</strong></li>
<li>Jacques Bibaï, Pierre Savéant, Marc Schoenauer, Vincent Vidal, <a href="">An Evolutionary Metaheuristic for Domain-Independent Satisficing Planning</a>, <i>Genetic and Evolutionary Computation Conference</i> (2010). <strong>Silver Medal at the Human-Competitive Competition</strong></li>
@ -994,16 +1015,6 @@ undiscovered knowledge.
physics/0603108 (2006)</a>.</li>
</ul>
<h3>Metaheuristics Design</h3>
<ul>
<li>Johann Dreo, <a href="https://dl.acm.org/doi/10.1145/1570256.1570301">Using Performance Fronts for Parameter Setting of Stochastic Metaheuristics</a>, <i>Genetic and Evolutionary Computation Conference</i>, (2009).</li>
</ul>
<h3>Accelerator Physics</h3>
<ul>
<li>E. Valetov, G. Dal Maso, P-R. Kettle, A. Knecht, A. Papa, on behalf of the HIMB Project. <a href="https://doi.org/10.3390/particles7030039">Beamline Optimisation for High-Intensity Muon Beams at PSI Using the Heterogeneous Island Model</a>. <i>Particles</i> <b>2024</b>, <i>7</i>, 683-691.</li>
</ul>
</div>
</div>